A simple approach is to re-use the hand-crafted prompts provided by CLIP which is originally designed for image classification on ImageNet-1K [1]}. There are 80 different prompts, each consisting of a natural sentence with a blank position for injecting the category names. Since these prompts are not originally designed for semantic segmentation, some of them may have a adverse effect. So we evaluate each of these prompts on training data to select one most helpful prompt for zero-shot semantic segmentation.
